This is a remote position.
As a Senior Data Scientist at Migo you will play a key role in optimising our machine learning-driven decision systems from monitoring and retraining existing models to developing new ones that power automated lending decisions. You will analyse performance data to refine features select optimal models for different customer segments and integrate new data sources into our modelling frameworks. Your work will combine statistical rigour with practical problem-solving leveraging causal inference concepts A/B testing and robust ETL pipelines to improve model accuracy and stability. Working closely with engineering and product teams you will ensure our decision-making systems remain adaptable data-driven and effective as we scale into new markets and serve a growing customer base.
Responsibilities
- Analyze business data to assess performance and identify areas for improvement
- Monitor retrain and iteratively improve machine learning models
- Add and remove features based on performance analysis
- Select optimal models for different customer segments using established metrics
- Integrate new data sources into existing modeling frameworks
- Analyze new data to develop rule-based and heuristic approaches
- Monitor and develop ETL and feature engineering pipelines
- Develop new ML models for automated decision-making
Requirements
You are a good fit if you have:
- An MS in Machine Learning Data Science Economics or (Applied) Statistics or equivalent experience
- Experience with ML lifecycle and statistical modeling
- Knowledge of ML concepts such as model drift and data leakage
- Experience developing new machine learning models
- Familiarity with basics of causal inference
- Experience with Python and object-oriented programming
- Experience in data pipelines and ETL processes
- Experience with A/B testing
- Full proficiency in SQL
- Experience with ML lifecycle and statistical modeling - Knowledge of ML concepts such as model drift and data leakage - Experience developing new machine learning models - Familiarity with basics of causal inference - MS in Machine Learning, Data Science, Economics, or (Applied) Statistics, or equivalent experience - Experience with Python and object-oriented programming - Experience in data pipelines and ETL processes - Experience with A/B testing - Full proficiency in SQL